S: All right, well, Cara, we're gonna start with What's the Word. And we have a follow up! This is, I think, our first follow-up word.

C: We got an email from a listener named Gary, who, after last week, when we talked about homeostasis said, I'll just quote a little, small part of it.

“A thermostat does not regulate a house to a specific temperature (that's homeostasis), but actually regulates to a temperature range based on hysteresis. Most furnaces have one level of thermal output – they're either on or off. The thermostat turns the furnace on at a temperature that's at the low point of the hysteresis band. The furnace runs until the temperature reaches the high point of the hysteresis band. And the cycle is repeated when the temperature reaches the low point again.”

So, Gary's making the distinction here between homeostasis and maybe a more specific term, which is hysteresis. So I want to jump into that term, hysteresis. It is a physics term. I think the most precise definition that I could find online was, “The lag in a variable property of a system with respect to the effect producing it as this effect varies, especially the phenomenon in which the magnetic flux density of a ferromagnetic material lags behind the changing external magnetic field strength.”

And the reason that you see magnets used a lot in a discussion of hysteresis online is because the term hysteresis was first described to delineate what actually happens in magnetic materials. But of course, that description has opened up quite a bit. You see it in engineering. Oftentimes, hysteresis is intentionally added to electronic circuits, or computer algorithms, either in electronics, to prevent unwanted rapid switching of a circuit, or in a computer algorithm, to kind of allow an interface to be more intuitive, because of course, our brain's processing speed can be a little bit slower than the computer's processing speed. So an intentional lag there will help you not have your hand be confused as to where it is on an interface, you know, if you're moving a mouse around, there will be a lag built in for you so it feels more intuitive.

You can also find examples of hysteresis in biology, material science, economics, a ton of other fields. (Deep breath) Oh, and the etymology of course of hysteresis (the most important part).

It's from the Greek term, hysteresis, which is a coming short, or a deficiency, which came from an earlier “hysteros,” meaning “later,” or “second,” or “after.” So, that kind of, sort of makes sense. Sir James Alfred Yeuing in the 1880's actually coined the term “hysteresis” to describe the behavior of magnetic materials. But you'll see a lot of other examples. A common one is a rubber band, that as you put weights on a rubber band, and then you remove those weights, and it snaps back. You see this kind of delayed physical response that is contingent on all of the previous historical stressors that you put on the material.

So, hysteresis seems to be this amalgamation of the way that a material reacts with regards to its history of external cues, and also, that there's this built in lag. Now, my question, to you guys, that is, do you think that that means that a thermostat, because it is a great example of hysteresis, is not a good example of homeostasis?

S: I was very intrigued by that distinction as well, and after doing as much reading on it as I had time to do in the last week, I think the best way to make sense of it is that hysteresis is the behavior of the thermostat itself, but that results in homeostasis. Homeostasis is a description of the environment. The environment itself is in homeostasis, with respect to temperature in that example. The temperature of the house, it regulates itself within a certain range.

I think that Gary was assuming that homeostasis means that the value has to be fixed at one specific value, and not have a range of values, and that is not true. Homeostatic systems can exist within a range.

C: Yeah, but that range is typically small.

S: Yeah, it's a small range, but there is no demarcation line, right? There's no line that you draw, right? It's like, your body temperature will vary by a couple degrees.

C: Yeah, and the reason that it can go higher or lower is happening, it's a kind of cascading effect, you know? At a certain height, or at a certain low point, you will see all sorts of things – proteins start to unfold – you'll see all sorts of things change in the body that, in full, can

S: Yeah

C: bring you to be very sick.

S: So, the hysteresis is almost like, that's like a mechanism, and the homeostasis is the result.

C: Gotcha.

S: I came across two other terms that were kind of related that I wanted to hit upon. One is “steady-state,” and the other is “dynamic equilibrium,” or equilibrium. And oftentimes, those two terms are confused with each other. Equilibrium is when – for the classic example is let's say you have a hot object in a large room, like a cup of coffee. And then when the coffee cools down so that it's the exact same temperature as the room that surrounds it, it's at thermal equilibrium. There's no longer any net heat exchange between the two things.

A steady state is different than that. If you had the cup of coffee on a hot plate, on a heating element, and then that hot plate would heat the coffee up by putting energy into it, but the more heat the plate puts into the coffee, the more heat goes from the coffee to the air. At some point, at some temperature, you're gonna reach steady state, where the heat going into the cup is equal to the heat going from the cup into the surrounding air, right? That's a steady state. The difference is in the steady state, heat is being exchanged. In equilibrium, there is no net exchange.

C: Yeah, there's no net energy transfer at all

S: Right

C: in equilibrium.

S: Yeah, so a steady state exists in a lot of examples as well. Like in biology, for example. So your body temperature reaches a quote-unquote steady state. You produce heat, you radiate heat. At some point, those two things are equal, and you're in a steady state. That produces the homeostasis of body temperature, you know what I mean?

So steady state has a same kind of relationship to homeostasis as hysteresis does. They're a component of the system that creates the overall environmental homeostasis.

C: So where do they think set point would fit into all of this?

S: Again, I think that it depends on context, but that's just the point at which you reach a steady state, right?

C: There you go.

S: Yeah

C: Yeah, I guess that's true. It would still require – you would still get to a point where there, it's constantly requiring energy to put into the system, to maintain that set point.

S: If you have to put energy in, then that's, you're at a steady state. If it's just passive, like there's no net exchange of energy, then that's equilibrium. And hysteresis is when the change, depends upon the history, like, is it coming up or going down? You know, so if you're putting a weight on or taking the weight off, but getting to the same point, the system behaves differently depending on what state you're coming from. That's why you have a hysteresis loop – you saw that when you were reading about it.

C: Yeah, yeah.

S: Where, it follows one path on the way up, and a different path on the way down. And you get a very characteristic loop. That's because the path that it's taking is dependent upon its recent history. That's the definition, I think, of hysteresis. And what I love about things like this is that it always reminds me of how deep any concept is.

C: Yeah

S: If you go down any rabbit hole, it goes down really deep. And we're, this treatment that we just did is very superficial.

C: Oh, completely.

S: Yeah yeah.

C: I still don't fully – I mean, after reading it for so long, I still don't fully understand it. And so it's interesting, because, obviously, we were coming at homeostasis from a biological place, and then using what we thought was a good real world example. But of course, we, in his view, were probably oversimplifying a thermostat.

S: Oh yeah. Well, the thing you have to realize, that we simplify everything we talk about. Whether we oversimplify it or not is kind of a judgment call. We're always, when you're explaining science to a general audience, you can't dive all the way down to the cutting edge, most technical knowledge.

I often have to remind medical students of this in residence. It's like, you just need to be aware, roughly, how deep the well of knowledge goes.

B: Oh, I totally agree. It's sobering. You think you have a decent handle on some technical topic, and then I find an article that is clearly written by a physicist, somebody who knows their shit

S: Yeah

B: so deep, and I just read a paragraph, I'm like, “What the hell? I thought I knew this! I really thought I had a handle on this, and clearly, it's superficial,”

S: Right

B: compared to these guys. And I think everybody should do that, who gets a little cocky sometimes. You just need to do that, to realize that you're just really scratching the surface.

S: We encounter pseudoscientists all the time. One of the consistent errors that pseudoscientists make, is that they don't appreciate the difference between their lay understanding of what's going on, and a real in depth, technical understanding of what's going on. They're confusing that superficial layer. And then, it is very much like children trying to argue with adults in terms of the difference of knowledge. And then they get all pissy when we don't take them seriously.

(Cara laughs)

B: Imagine being one of those

E: Yep

B: few people that are on the cutting edge of their discipline, and really, they could genuinely say to themselves, “Yup, nobody knows this any deeper than I do right now.” That must be an incredibly rewarding, I would think.

S: All right, well, let's move on with some news items. This item, I think was the most interesting one of the week. A study came out, comparing male and female brains. The researchers had a very specific question. They wanted to know if there are any categorical differences between male and female brains.

They looked at four data sets of MRI scans and fMRI scans, so, both looking at anatomy, as well as connections, like, networks in the brain, where you could make comparisons between men and women. And they found some very interesting results.

Their results, the bottom line reporting of the results, a lot of the headlines said something along the lines of, that the research showed there was quote-unquote “no difference” between male and female brains. That's not quite right.

J: That's way too general, right?

S: Yeah, that's not quite right. It's actually, again, we get to a similar difference between homeostasis and hysteresis, right? We're getting to a technical level. But I do think it's important, because categorization is a basic skill in thinking about reality, the universe, and science. It's good to think about how we categorize things. It's like, in medicine, I try to teach my students, how do we define diseases, right? How do we define clinical entities. If you don't understand that, then you can't really think about them.

Let's back up a little bit, and first talk a little bit about how we define different categories. For example, we could talk about, how do we define the category of a planet, right? This was a controversial topic that came up a few years ago with Pluto. Astronomers had to decide how they were going to define “planet” as a category. Also, historically, I think another great example is biologists categorizing ten million species. How're we gonna define life on Earth? How are we gonna categorize stuff?

This is where things get tricky, because the universe is fuzzy, right? Categories in reality are complicated, they're blurry at the edges, there's exceptions, et cetera.

C: They're also dependent on technology.

S: Yeah, it's dependent on lots of things, on our ability to describe and examine things, and also on our understanding of the underlying principles. So ideally, the best categorization system would have unambiguous categories that follow some kind of objective operational definition, and reflect our understanding of the underlying science.

If you know how planets form, you can use that knowledge to decide how to categorize solar system objects. That's not quite how they did it. They used easily definable milestones, like if a body is big enough to pull itself into a sphere, that's one criterion; or if it is big enough to clear out its local space, like, does it gravitationally dominate its orbit. Those were easily definable, operational definitions, but they don't necessarily reflect a real distinction between how these objects come about. In this case, we have essentially a spectrum, a continuum, and you're just drawing a line somewhere along that continuum based on some physical property that we can define.

B: Which is often arbitrary.

S: Which is often arbitrary. What physical properties are you gonna decide to use as your milestones?

Okay, so let's turn to male and female brains. The authors are making a distinction between a categorical difference, and a statistical difference. And they used as an example of a categorical difference, genitalia. In terms of male and female genitalia, we basically have a sexually dimorphic or bimodal system. You have male genitalia and female genitalia. There's no third thing, there's nothing else. And most people can be unambiguously placed in one category or the other, and there's essentially no overlap in between.

However, there are exceptions. You know, there are biological exceptions. There's a number of conditions that can result in what we call ambiguous genitalia. Either genetic, hormonal, developmental, et cetera. But I think it's reasonable to consider those anomalies, and they are the exception, not the rule. The rule still is for the vast majority of people, there are two states. And you can unambiguously place people in one of those two states. So there are categorical differences.

So, the researchers wanted to know, are there categorical differences between male and female brains? Another way to look at the difference between a categorical versus a statistical difference, if you know what category an individual belongs to, does that tell you anything absolutely about their traits?

B: Ah!

S: So, knowing that somebody is male will enable you to predict with a very high reliability, what genitalia they have.

C: Gotcha.

S: Of course, again, with the exceptions, but it's a pretty good predictor of their genitalia.

C: You were talking about, when you were first defining male and female genitalia, you were saying specifically that you could put a male or female label on the genitalia, not on the person's psychological representation of self.

S: Not their identity, not their sexual orientation, not anything else; just their biologically.

C: My question is, can you flip that? So, is a categorical definition one that if you were to hand me a brain – just a brain – and I looked at it, I could categorically say, “This is in the skull of a male human or a female human” based on its features?

S: So, let's get to the data of the study.

C: Yeah

S: What they found – it's very interesting. They looked at about forty different anatomical or functional aspects of the brain. And what they found was that generally speaking, there are statistical differences between males and females when you look at specific, like, the size of one anatomical region, or the robustness of a network or connection between two regions.

Now, you could say, “Yeah, there's a statistical difference.” However, there's a lot of overlap, right? So they're not categorically different, they're just statistically different. And sometimes they could even be slight. But because you're dealing with such large numbers of individuals in these four data sets, you can get statistical significance even for very small differences.

B: And Steve, couldn't some of these differences be related not to pure biology, or whether you're male or female, but to things like environment and culture, which we know the brain interacts with the environment and culture, and is shaped by it in many ways.

S: Yes, so that is a separate question that was not even addressed by this study.

C: Oh wow.

S: This study's not looking at what is causing any differences that they're seeing, only whether or not there are differences, which is an easier question to address. It's really hard to tease apart culture versus biological, environmental, et cetera. But then they did another analysis, where they looked at individuals, and they said, if in an individual, what percentage have mostly, like if you look at an individual male subject, how many of their forty brain regions will be typically male? And how many will be typically female or somewhere in the middle?

So, one way to capture that data, say, well, what percentage of people a hundred percent of their brain regions are typical for their sex? And among the four data sets, that number ranged from zero to eight percent. So, very few people, like, very few men have all male brain regions

C: Wow

S: in terms of their size and connections. How many have a mixture of both, was like, twenty-eight to fifty-eight percent. So, over all, what they found was that while there are statistical differences in specific aspects of the brain, there's a lot of overlap, and that when you look at individuals, people are mosaics. And most people are a mosaic of male and female traits. Does that make sense?

C: Yeah

E: Steve, does that continue with the line of research to do, or is that different? Is this a new discovery?

S: I don't know that this is new, but this is just looking back at previous data sets. But, a lot of research will look at one aspect, you know, will look at, “Oh! Let's look at brokezarian, and see, you know, if it's any difference between men and women, and say, 'Oh look! A statistical difference.'” But this was the first to put it all together, that I'm aware of, to put it all together, and then to look at individuals and say, “What do individuals look like?”

So, another way to look at this, getting back to the previous question is, if I know somebody is male, can I predict anything about their brain regions? And the answer is no!

B: (Chuckles) No!

S: You can't! That doesn't predict anything about – 'cause they could have half of their brain regions could be typically female!

J: Steve,

C: Wow

J: you can't detect the effect that hormones have on ...

S: Well, yeah, that's yet a separate question. But of course hormones affect the brain, like testosterone and estrogen. That is true, but that is, you're getting now into the causes of differences that are there.

What the authors concluded was that there isn't a typical male or a typical female brain like there is typically male or typically female genitalia. Their things are not analogous. That individuals are mosaics, and whether they're male or female doesn't really predict much about their individual brain. But there are statistical difference between the sexes, but they don't predict individual characteristics.

C: So I often see this story. You know, I see the headline of “Are Male and Female Brains Different?” It keeps popping up. And I remember covering it previously, and often seeing that there are categorical distinctions. Do you think that the difference with this study is that instead of looking at individual brain regions in a vacuum, they decided to aggregate all of them, and determine whether or not an individual fits into that aggregate pattern?

S: Yeah, exactly. That's what they're doing. And it was trying to address the specific question, is there a typical male and a typical female brain, and the answer is clearly no.

C: I wonder how male my brain is?

S: The bottom line of all of this is that people are individuals. Knowing that somebody is a male or female doesn't tell you that much about them neurologically or mentally, certainly not as much as you might think. What's interesting is that the more you sort of delve into this question, the more you discover, in my experience, that stereotypes are just that. They're actually stereotypes, like the idea that women aren't as much into geeky things. That's not true! Plenty of women who are nerds, and into all the geeky stuff that we're into.

I remember I took personality inventory, and it was designed in the fifties. And one of the questions was, “Do you like flowers?” I'm like, “Sure, I love flowers.”

(Cara laughs)

E: How do you like them flowers?

S: And the study interpreted that as a characteristic of being homosexual.

hi guys, I'm a genome scientist and one of my areas of interest is horizontal gene transfer, which was the subject of last week's SorF, when you discussed the new PNAS paper on the tardigrade genome. That paper made the incredible claim that 17% of the animal's genome had been laterally transferred, mostly from bacteria. I was very skeptical, having published papers before debunking such claims (the PNAS paper actually referenced my work), so I read the paper right away. I'm working with a few colleagues to see if we can confirm or debunk their claims. But meanwhile, another group was nearly done sequencing another tardigrade genome, and they just published a preprint on biorXiv *today* (http://biorxiv.org/content/early/2015/12/01/033464), in which they repudiate the claim of the PNAS paper. Their abstract says 'We compare our assembly to a recently published one for the same species and do not find support for massive horizontal gene transfer.' One reason I was so skeptical of the PNAS paper is that the assembly of the genome is terrible - it's in many thousands of small pieces. This means many of those pieces could be contaminants - there's no sequence connecting them to the rest. In addition, the genome they describe is too big, at 200 megabases. The same group published a paper in 2007 estimating the genome size as much smaller, and this new biorXiv paper reports a genome of 130 Mb. I think you should update the SorF segment to correct this - I seriously doubt that this claim will hold up. Horizontal gene transfer (HGT) involving animals is extremely rare and this new paper isn't going to change that paradigm. I think they were looking for a headline to get their paper into PNAS, as often happens. That didn't take long! Steven Salzberg, PhD Baltimore, MD

Item #1: In Iceland they have 13 Yule Lads instead of one Santa Claus, whose mother, Gryla, kidnaps naughty children and cooks them in a cauldron.
Item #2: The modern look of Santa Claus was essentially invented by Coca Cola in the 1930’s; prior to that Saint Nick was most often portrayed as tall and thin.
Item #3: Due to a wildly successful marketing campaign in 1974, KFC is the most popular meal for Christmas dinner in Japan.

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